1. Technical Field
The present invention relates to medical image analysis, and more particularly, to a system and method for visualizing pulmonary emboli from high-resolution computed tomography (CT) images.
2. Discussion of the Related Art
A deep vein thrombosis (DVT) is a blood clot in a vein located deep in the muscles of the legs, thighs, pelvis or arms. A pulmonary embolism occurs when a piece of a blood clot from a DVT breaks off and travels to an artery in a lung where it blocks the artery and damages the lung. This short-term complication is potentially life threatening and occurs in about 10% of patients with acute DVT events. It may be even more common than generally realized because a majority of embolisms occur without symptoms.
Several factors are known to cause DVTs, these are: an injury to the vein, slowing of blood flow and conditions that increase the tendency for the blood to clot. The most common cause of an injury to a vein is a trauma to the leg such as that which occurs with broken bones, severe muscle injury or surgery. Immobilization is the most common cause of slow blood flow in a vein as movement of the leg muscles helps to keep blood flowing through deep veins.
The majority of people recover fully from a DVT and pulmonary embolism. However, a large pulmonary embolism can block almost all of the blood flow to the lungs and cause sudden death. In addition, a pulmonary embolism can put a severe strain on the heart. A pulmonary embolism is a common disorder with an annual incidence rate of 23 to 69 per 100,000 people in the United States. Up to 60,000 Americans each year die because of a pulmonary embolism. After ischemic heart disease and stroke, a pulmonary embolism is the third leading cause of death from heart disease, and may be the most common preventable cause of death in hospitals. Further, in at least two-thirds of cases, a pulmonary embolism had not been suspected prior to death.
A pulmonary embolism is a difficult disease to diagnose as the symptoms are non-specific. Many patients with a pulmonary embolism are never examined and the majority of patients suspected of having a pulmonary embolism do not have the disease. A pulmonary embolism is often, but not invariably, associated with lower extremity venous thrombosis. Prompt diagnosis of pulmonary embolism is a major concern because an untreated pulmonary embolism is potentially fatal. Accurate diagnosis is also important because unnecessary treatment with anticoagulants has been shown to have a high degree of morbidity and mortality.
Contrast-enhanced computed tomography (CT) techniques are increasingly being used to diagnose a pulmonary embolism. In such techniques, a contrast agent such as an iodine-containing dye is injected into an arm vein of a patient while the patient is scanned in a spiral CT scanner during a single breath-hold. This scan is very rapid, typically taking less than 30 seconds, and the resulting images are frequently returned to a doctor within 30 minutes of the scan being ordered. Other advantages of a spiral CT scan are its non-invasive nature and its effectiveness at diagnosing the majority of pulmonary emboli that are in the main branches of the pulmonary arteries. In addition, a spiral CT scan directly shows a clot obstructing a vessel or contrast streaming around a partially occluded embolus. Further, the spiral CT scan shows the parenchymal changes of a pulmonary embolism better than radiographs, and often provides an alternative diagnosis when a pulmonary embolism is not present.
Earlier generations of spiral CT scanners performed poorly in detecting pulmonary emboli in the smaller arteries of the lung in which 16 to 30% of all pulmonary emboli occur. The recent introduction of 16-slice spiral CT machines has enabled patients to be scanned in sufficiently high detail to allow physicians visualize the smaller arteries to confirm or rule out the presence of an embolus. However, the large size of these datasets, typically around 5123 points, has increased the time it takes to analyze CT images. Accordingly, there is a need for an automated technique that rapidly and accurately locates pulmonary emboli candidates in large CT datasets.